Autopoietic-extended architecture: can buildings think?

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Abstract

To incorporate bioremedial functions into the performance of buildings and to balance
generative architecture's dominant focus on computational programming and digital
fabrication, this thesis first hybridizes theories of autopoiesis into extended cognition in order to
research biological domains that include synthetic biology and biocomputation. Under the
rubric of living technology I survey multidisciplinary fields to gather perspective for student
design of bioremedial and/or metabolic components in generative architecture where
generative not only denotes the use of computation but also includes biochemical,
biomechanical, and metabolic functions.
I trace computation and digital simulations back to Alan Turing's early 1950s
Morphogenetic drawings, reaction-diffusion algorithms, and pioneering artificial intelligence
(AI) in order to establish generative architecture's point of origin. I ask provocatively: Can
buildings think? as a question echoing Turing's own "Can machines think?" Thereafter, I
anticipate not only future bioperformative materials but also theories capable of underpinning
strains of metabolic intelligences made possible via AI, synthetic biology, and living technology.
I do not imply that metabolic architectural intelligence will be like human cognition. I
suggest, rather, that new research and pedagogies involving the intelligence of bacteria, plants,
synthetic biology, and algorithms define approaches that generative architecture should take in
order to source new forms of autonomous life that will be deployable as corrective
environmental interfaces. I call the research protocol autopoietic-extended design, theorizing it
as an operating system (OS), a research methodology, and an app schematic for design studios
and distance learning that makes use of in-field, e-, and m-learning technologies.
A quest of this complexity requires scaffolding for coordinating theory-driven teaching
with practice-oriented learning. Accordingly, I fuse Maturana and Varela's biological autopoiesis
and its definitions of minimal biological life with Andy Clark's hypothesis of extended cognition
and its cognition-to-environment linkages. I articulate a generative design strategy and student
research method explained via architectural history interpreted from Louis Sullivan's 1924
pedagogical drawing system, Le Corbusier's Modernist pronouncements, and Greg Lynn's
Animate Form. Thus, autopoietic-extended design organizes thinking about the generation of
ideas for design prior to computational production and fabrication, necessitating a fresh
relationship between nature/science/technology and design cognition. To systematize such a
program requires the avoidance of simple binaries (mind/body, mind/nature) as well as the
stationing of tool making, technology, and architecture within the ream of nature. Hence, I argue,
in relation to extended phenotypes, plant-neurobiology, and recent genetic research:
<Architecture = Nature>
Consequently, autopoietic-extended design advances design protocols grounded in morphology,
anatomy, cognition, biology, and technology in order to appropriate metabolic and intelligent
properties for sensory/response duty in buildings.
At m-learning levels smartphones, social media, and design apps source data from
nature for students to mediate on-site research by extending 3D pedagogical reach into new
university design programs. I intend the creation of a dialectical investigation of animal/human
architecture and computational history augmented by theory relevant to current algorithmic
design and fablab production. The autopoietic-extended design dialectic sets out ways to
articulate opposition/differences outside the Cartesian either/or philosophy in order to
prototype metabolic architecture, while dialectically maintaining: Buildings can think.